Papers with aspect based sentiment analysis
Adversarial Sample Generation for Aspect based Sentiment Classification (2022.findings-aacl)
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| Challenge: | Existing approaches to attack adversarial samples in natural language processing are ineffective . initial attacks perturb characters or words in sentences, resulting in grammatical incorrect or out-of-context sentences. |
| Approach: | They propose an attack algorithm that generates adversarial samples for a given aspect, maintaining more semantic coherency. |
| Outcome: | The proposed method outperforms the state-of-the-art methods in perturbation ratio, success rate, and semantic coherence. |
Aspect-Category based Sentiment Analysis with Hierarchical Graph Convolutional Network (2020.coling-main)
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| Challenge: | Aspect-based sentiment analysis studies focus on identifying sentiment polarities toward explicit aspects but ignore implicit aspects in text. |
| Approach: | They propose a hierarchy-sentiment hierarchy prediction problem to capture explicit and implicit aspects of aspect-based sentiment analysis. |
| Outcome: | The proposed model can consistently achieve the best results on four benchmarks. |
Dataset Creation and Evaluation of Aspect Based Sentiment Analysis in Telugu, a Low Resource Language (2020.lrec-1)
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| Challenge: | Aspect Based Sentiment Analysis (ABSA) is a finer level sentiment analysis that assigns polarity to each targeted aspect instead of the entire review. |
| Approach: | They propose to use Telugu as a language for aspect based sentiment analysis . they use a resource that can be used to classify and categorise aspects of a review . |
| Outcome: | The proposed resource is based on a set of tasks in Telugu which demonstrate its reliability and usefulness. |
A deep-learning framework to detect sarcasm targets (D19-1)
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| Challenge: | Existing methods for sarcasm target detection are difficult to implement in natural language processing. |
| Approach: | They propose a deep learning framework for sarcasm target detection in predefined sarkastic texts. |
| Outcome: | The proposed framework improves accuracy and accuracy in match and dice scores compared to the current state-of-the-art framework. |
Introducing Syntactic Structures into Target Opinion Word Extraction with Deep Learning (2020.emnlp-main)
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| Challenge: | Current deep learning models fail to exploit syntactic information of sentences . proposed model incorporates syntax-based opinion possibility scores and syntaktic connections between the words . |
| Approach: | They propose to incorporate syntactic information of sentences into deep learning models for TOWE . they propose a novel regularization technique to improve the performance of the models . |
| Outcome: | The proposed model achieves state-of-the-art on four benchmark datasets. |